Through the Crystal Ball: Risk Scores and Imprecision in Medicine (Guest Post)

hands hold up a small ball of snow, shaped like a heart.

He was forty-nine and he had no past medical history, no family history of coronary artery disease, and no risk factors (known or measurable) for coronary artery disease. He ate healthier than most people. I have to admit that I don’t really miss the green smoothie he made for us every single morning. He saw his primary care physician at least every other year, and got his flu shot every year. He worked out 6 days a week and he was fitter than the vast majority of people I know. He would show off to friends in his gym – “not bad for fifty!”

Two years prior to his death, his American College of Cardiology risk score would have been 4%, and his Framingham risk score would have been 9%, meaning that he had a 4-9% risk over the next ten years for having a myocardial infarction or stroke or death from coronary artery disease. Even if the slim data for preventing acute coronary syndrome in those who have never had a myocardial infarction were to be acted upon, his risk would have been reduced by 20-30% if he was treated with statin. That would have meant that his ten-year risk would be reduced from 9% to between 6.3% and 7.2%, or from 4.2% to between 2.9% and 3.4%. These prediction scores do not factor in potential risk factors such as genetic predisposition, and they do not include potentially protective factors such as emotional well-being. There is no good way to assess genetic predisposition or emotional well-being anyway. His primary care physician did not think statins were indicated for primary prevention in his case. There simply isn’t much evidence.

His presentation didn’t allow us an opportunity for early diagnosis or treatment. He was supposed to be recovering from a respiratory virus. His red flag symptom was “something is wrong”. He passed away within 35 minutes of saying this. Of late, I have been reading a lot about prediction models for cardiac disease, complicated atherosclerotic plaques, ‘vulnerable’ plaques and progression of plaques. In spite of the numerous advances in the field of acute coronary syndrome, there are several unanswered questions. Per the excellent review article in JAMA Cardiology (reference below), the critical determinants that cause one vulnerable plaque to cause a clinical event but another vulnerable plaque to be silent and heal are unknown. It turns out that the area of a plaque as visualized by coronary ultrasound gives a more realistic picture of the extent of disease than the more common coronary angiography test that only shows percent narrowing of the lumen. There is no practical way to diagnose presence of an atherosclerotic plaque in a person without symptoms, and it is not known why some plaques progress rapidly while others progress at a much slower pace. The role of genetic testing to personalize treatment plans and improve patient outcomes is not known either.

These are my professional takeaways from my life-shattering experience. A lot of serious health events occur in the community before we see patients in the hospital. We need more population based studies that represent diverse populations. Because South Asian men are known to have a greater genetic predisposition, we would need prediction models specifically applicable to this population. If you check the inputs into any prediction score, one will realize that they don’t account for a lot of factors which might influence the outcome. We as physicians need to accept and acknowledge imprecision in medicine. Outcomes such as survival (or death) for patients and their loved ones are binary. There is no such thing as 4% or 9% death. It’s either 100% or 0% for that particular individual. We do not have sufficient medical knowledge to identify those 4 or 9 individuals among hundred who indeed would have a bad outcome, let alone customize prevention and treatment plans. We are challenged with articulating this risk to patients and specifically what a particular risk score means to each of them. Both physicians and patients need to understand and accept limitations of medical knowledge without losing faith in the power of medicine to save lives.


 

Pranavi Sreeramoju, MD, is a physician in Dallas working in a busy academic healthcare environment. Her expertise is in infectious diseases, epidemiology, quality and patient safety. She blogs at PranaviMD.com.


Suggested Additional Reading:

  1. Updates on Acute Coronary Syndrome: A Review. Alon Eisen, Robert P. Giugliano, Eugene Braunwald. JAMA Cardiol. 2016;1(6):718-730. http://jamanetwork.com/journals/jamacardiology/article-abstract/2536031
  2. Assessing the performance of prediction models: a framework for some traditional and novel measures. Ewout W. Steyerberg, Andrew J. Vickers, Nancy R. Cook, Thomas Gerds, Mithat Gonen, Nancy Obuchowski, Michael J. Pencina, and Michael W. Kattan. Epidemiology. 2010 Jan; 21(1): 128–138. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3575184/

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